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Gerard Ledwich

Researcher at Queensland University of Technology

Publications -  691
Citations -  17432

Gerard Ledwich is an academic researcher from Queensland University of Technology. The author has contributed to research in topics: Electric power system & AC power. The author has an hindex of 56, co-authored 686 publications receiving 15375 citations. Previous affiliations of Gerard Ledwich include University of Wollongong & University of Tabriz.

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Power Quality Enhancement Using Custom Power Devices

TL;DR: Power Quality Enhancement Using Custom Power Devices as discussed by the authors considers the structure, control and performance of series compensating DVR, the shunt DSTATCOM and the SHunt with series UPQC for power quality improvement in electricity distribution.
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Improvement of Stability and Load Sharing in an Autonomous Microgrid Using Supplementary Droop Control Loop

TL;DR: In this article, a supplementary loop is proposed around a conventional droop control of each DG converter to stabilize the system while using high angle droop gains, which is formulated as a parameter optimization problem and solved using an evolutionary technique.
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Optimal Planning of Electric-Vehicle Charging Stations in Distribution Systems

TL;DR: In this article, a mathematical model for the optimal sizing of EV charging stations is developed with the minimization of total cost associated with EVs charging stations to be planned as the objective function and solved by a modified primal-dual interior point algorithm (MPDIPA).
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Renewable energy sources and frequency regulation: survey and new perspectives

TL;DR: In this article, an overview of the key issues and new challenges on frequency regulation concerning the integration of renewable energy units into the power systems is presented, followed by a brief survey on the existing challenges and recent developments, the impact of power fluctuation produced by variable renewable sources (such as wind and solar units) on system frequency performance is also presented.
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Optimal Siting and Sizing of Distributed Generators in Distribution Systems Considering Uncertainties

TL;DR: In this article, a chance constrained programming (CCP) framework is presented to handle the uncertainties in the optimal siting and sizing of distributed generators in distribution system planning, and a Monte Carlo simulation-embedded genetic-algorithm-based approach is employed to solve the developed CCP model.